中文摘要：

对中医临床诊断数据的特性进行了研究,提出了病证及其特征数据（症状或体征数据）的一些特性指标：病证的相似度、复杂度、隐蔽度,特征数据的贡献度、常见度、显隐性。另外,研究了基于多维关联规则提取诊断经验的方法。在此基础上,研究了一种非充分条件下复杂数据智能化处理拓展算法,该算法的实现模型嵌入了模糊竞争神经网络。该算法在复杂的中医诊断数字化中得到了应用,结果表明,该算法可以较好地处理复杂数据。

英文摘要：

Some characteristics of traditional Chinese medicine（TCM） clinical diagnosis data are researched,and some characteristic parameters of the diseases and its character data（symptoms or physical signs） are presented including Disease＇s similarity degree,and its complexity degree,and its invisibility degree,and the character data＇s contribution degree,rate of appearance,external（or pre-sentational） and invisible character.In addition,the means of providing diagnosis experiences for doctor based on the multidimensional association-rule mining algorithm is researched.On the basis of these,an intelligent processing expandable algorithm on incomplete and complex data is researched.The algorithm＇s implementing model embedded fuzzy competition neural network.The algorithm had obtained application in the complex digitization of traditional Chinese medicine diagnosis.The application result show the algorithm can processed preferably perplexed data.